U.S. patent number 5,757,496 [Application Number 08/812,598] was granted by the patent office on 1998-05-26 for method of surface roughness measurement using a fiber-optic probe.
This patent grant is currently assigned to Mitutoyo Corporation. Invention is credited to Kazuo Yamazaki.
United States Patent |
5,757,496 |
Yamazaki |
May 26, 1998 |
**Please see images for:
( Certificate of Correction ) ** |
Method of surface roughness measurement using a fiber-optic
probe
Abstract
A method of surface roughness measurement is disclosed which
uses a fiber-optic probe having a sensor head constituted of a
light-emitting fiber and multiple light-receiving fibers disposed
coaxially with the light-emitting fiber. The surface roughness
measurement includes the steps of: (a) pre-measuring a first
correlation between detected intensity and gap distance for each of
reference samples obtained under a plurality of different
processing conditions; (b) searching a second correlation between
maximum intensity and surface roughness for each of the reference
samples, based on the first correlation, and storing the second
correlation in memory; (c) adjusting the gap distance so as to set
the probe in a position at which the maximum intensity is obtained
for the reference sample machined under the processing condition to
be monitored; and (d) monitoring the maximum intensity of the
machined surface at the gap distance set in step (c), and
determining the roughness of the machined surface based on the
second correlation.
Inventors: |
Yamazaki; Kazuo (El Macero,
CA) |
Assignee: |
Mitutoyo Corporation
(JP)
|
Family
ID: |
25210076 |
Appl.
No.: |
08/812,598 |
Filed: |
March 7, 1997 |
Current U.S.
Class: |
356/600 |
Current CPC
Class: |
G01B
11/303 (20130101) |
Current International
Class: |
G01B
11/30 (20060101); G01B 011/30 () |
Field of
Search: |
;356/371,373,376,445,446
;250/227.11,227.21,227.23,227.28,227.24,231.1 ;385/12 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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|
|
|
|
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|
0071609 |
|
Apr 1988 |
|
JP |
|
1315803 |
|
Jun 1987 |
|
SU |
|
Other References
"The fiber-optic instrument for extremely small roughness
measurement", A. Domanski et al., SPIE vol. 670 Optical Fibres and
Their Applications IV (1986), pp. 116-118. .
"A novel non-contact sensor for surface topography measurement
using a fibre optic principle", Clive Butler and Gregorios
Gregoriou, Sensors and Actuators A. 31 (1992), pp. 68-74. .
"The method of surface roughness measurement with application of
optical fibers", Andrzej W. Domanski et al., SPIE vol. 670 Optical
Fibres and Their Applications IV (1986), pp. 119-112..
|
Primary Examiner: Pham; Hoa Q.
Attorney, Agent or Firm: Webb Ziesenheim Bruening Logsdon
Orkin & Hanson, P.C.
Claims
What is claimed is:
1. A method of surface roughness measurement using a fiber-optic
probe wherein said probe has at least one sensor head constituted
of a light-emitting fiber and multiple light-receiving fibers
disposed coaxially with the light-emitting fiber, the method
comprising the steps of:
(a) directing a light beam from the sensor head onto each of
multiple reference samples machined under a plurality of different
processing conditions, and pre-measuring a first correlation
between detected intensity and gap distance for each of the
reference samples, the detected intensity being defined as a sum of
outputs of the light-receiving fibers, the gap distance being
defined as a distance between the sensor head and a surface of the
reference sample;
(b) searching a second correlation between maximum intensity
defined as a peak of the detected intensity in a predetermined
range of the gap distance and surface roughness, based on the first
correlation obtained in step (a), and storing the second
correlation in a memory;
(c) adjusting the gap distance so as to set the probe in a position
at which the maximum intensity is obtained, based on the first
correlation for the reference sample machined under the processing
conditions to be monitored; and
(d) monitoring detected intensity obtained at the gap distance set
in step (c) for a to-be-measured sample, and determining surface
roughness thereof based on the second correlation stored in the
memory in advance.
2. The method according to claim 1, wherein
the sensor head comprises the light-emitting fiber and eight
light-receiving fibers disposed coaxially therewith, four of the
light-receiving fibers being symmetrically disposed on a first axis
passing through a light-emitting surface of the light-emitting
fiber to lie on opposite sides of the light-emitting fiber and the
remaining four of the light-receiving fibers being symmetrically
disposed on a second axis perpendicular to the first axis to lie on
opposite sides of the light-emitting fiber.
3. The method according to claim 1, wherein
the fiber optic probe is attached to a machine tool, and
the monitoring step (d) is performed during a machining process of
the machine tool.
Description
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to a method of surface roughness measurement
using a fiber-optic probe, more particularly to an effective method
of on-line surface roughness monitoring in various machining
processes.
2. Prior Art
Surface roughness monitoring is an important aspect of quality
assurance of manufacturing processes. Besides, surface roughness
can also be used as an indicator for diagnosing deterioration
factors such as tool wear and vibration of machining process as
well.
Recent evolution of machine tools is achieving higher accuracy and
higher productivity by utilizing high speed and intelligent
functions. This allows more integrated machining operation in a
single process with shorter machine time. Since sophisticated
geometry can be machined in a short time, it is important to check
the quality of the machined workpiece and to diagnose the machining
process right after the workpiece comes out from the machining
process and before goes to next process. In order to realize
time-efficient production and process quality control while keeping
highest productivity possible, high-speed, on-line or in-process
quality monitoring system is critical.
From such a viewpoint, a fiber-optic based non-contact surface
roughness measuring method is proposed, which is simple, fast and
easy to implement and easy to perform on-line measurement.
The fiber-optic method was proposed by A. W. Domanski, M. A.
Karpierz et al. in 1986 (A. W. Domanski, M. A. Karpierz, T. J.
Rzysko, 1986, The method of surface roughness measurement with
application of optical fibers, SPIE Vol. 670 Optical Fibers and
Their Application IV, 119-122). In their system, light from a low
coherence diode should be coupled to a multi-mode fiber, a
detecting multi-mode fiber is held symmetrically. Based on some
assumptions such as certain kind of surface model etc. and some
simplification, a simple relation between the scattering light
intensity and certain roughness parameters such as rms roughness
slope Rq can be obtained theoretically and experimentally.
In the same year, A. W. Domanski, W. Ejehart et al. proposed
another fiber-optic method (A. W. Domanski, W. Ejehart et al.,
1986, The fiber-optic instrument for extremely small roughness
measurement, SPIE Vol. 670 Optical Fibers and Their Applications
IV, 116-118). This method works in the range of profile mean
deviation 20 nm<Ra<150 nm. In this method, light is led by
the fiber to the surface and is analyzed by other fiber fixed in a
focal plane of the lens. This method is used to check the base
plate in microelectric semiconductor techniques. Since the
amplitude of the measured signal is greatly dependent on the
reflection properties of the material the surface is made of,
calibration is need.
In 1989, A. W. Domanski, T. R. Wolinski et al. proposed a
fiber-optic surface roughness measurement method based on
polarization measurements (A. W. Domanski, T. R. Wolinski et al.,
1989, Fiber-optic surface roughness sensor based on polarization
measurements, SPIE Vol. 1169, Fiber Optic Laser Sensors VII,
558-566).
Clive Butler and Gregorios Gregoriou in 1992 proposed a fiber-optic
sensor for surface topography measurement (Clive & Gregorios
Gregoriou, 1992, A novel non-contact sensor for surface topography
measurement using a fiber-optic principle, Sensors and Actuators
A.31 (1992) 68-72) and in 1994 reported the performance evaluation
of the sensor (Clive & Gregorios Gregoriou, 1994, Performance
evaluation of a novel non-contact fiber-optic triggering probe for
surface-topography measurement, Sensors and Actuators A.41-42
(1994), 98-101). In this system, a beam emitted by a laser diode at
the side surface is split by a beam splitter and directed onto the
sample surface as a 150 .mu.m spot using a lens. Light reflected
from the surface passes through a beam splitter and is collected at
a fiber bundle. The correlation between the detected light
intensity and the distance from the sensor focal plane to the
measured surface can be obtained. Theoretical model of this method
is based on geometric optics of lens. This method is used to
measure the surfaces of nylon, acrylic resin and various other
materials, but they only measured only surface step height around
500 .mu.m and no any surface roughness parameters were
involved.
It has been reported that using a fiber-optic sensor to observe the
diffraction pattern of a surface-machined sample enables easy
identification of a machined surface (Shetty, D., and Neault, H.,
1993, Method and Apparatus for Surface Roughness Measurement Using
Laser Diffraction Pattern, U.S. Pat. No. 5,189,490).
SUMMARY OF THE INVENTION
An object of the invention is to provide a method of surface
roughness measurement that enables monitoring of surface roughness
unaffected by the texture orientation of the machined surface
utilizing a simple and inexpensive fiber-optic probe and,
particularly, to such a method that can be advantageously applied
to on-line measurement of the machining process.
The method of surface roughness measurement using a fiber-optic
probe according to the present invention, wherein said probe has at
least one sensor head constituted of a light-emitting fiber and
multiple light-receiving fibers disposed coaxially with the
light-emitting fiber, the method comprising the steps of: (a)
directing a light beam from the sensor head onto each of multiple
reference samples machined under a plurality of different
processing conditions, and pre-measuring a first correlation
between detected intensity and gap distance for each of the
reference samples, the detected intensity being defined as a sum of
outputs of the light-receiving fibers, the gap distance being
defined as a distance between the sensor head and a surface of the
reference sample; (b) searching a second correlation between
maximum intensity defined as a peak of the detected intensity in a
predetermined range of the gap distance and surface roughness,
based on the first correlation obtained in step (a), and storing
the second correlation in a memory; (c) adjusting the gap distance
so as to set the probe in a position at which the maximum intensity
is obtained, based on the first correlation for the reference
sample machined under the processing conditions to be monitored;
and (d) monitoring detected intensity obtained at the gap distance
set in step (c) for a to-be-measured sample, and determining
surface roughness thereof based on the second correlation stored in
the memory in advance.
In accordance with the present invention, there is obtained a
non-contact method of surface roughness measurement using a
fiber-optic probe. A standard surface and a machined surface were
used to confirm the effectiveness of the invention and a good
correlation was obtained between the detected light intensity and
surface roughness. The conclusion was that the method of this
invention is effective as an on-line surface roughness monitoring
method applicable to a production machining system such as a CNC
machining center.
BRIEF DESCRIPTION OF THE DRAWINGS
FIGS. 1A and 1B are a sectional view and a bottom view of a
fiber-optic probe 1 used in an embodiment of this invention;
FIGS. 2A and 2B are a front sectional view and a bottom view of the
sensor head of the same probe;
FIG. 3 shows a measurement system of this embodiment;
FIGS. 4A, 4B and 4C show reflection modes of different sample
surfaces;
FIGS. 5A, 5B and 5C show elliptical distribution of scattered
reflected light;
FIG. 6 shows the relationship between the illuminating beam and
reflected light intensity distribution;
FIGS. 7A and 7B show a measurement method for reflected light
intensity measurement;
FIG. 8 shows the principle of reflected light intensity
detection;
FIG. 9 shows the correlation between detected intensity and
elliptical distribution;
FIG. 10 shows surface texture orientation;
FIGS. 11A and 11B show the relationship between detected intensity
and gap distance with surface texture orientation as a
parameter;
FIGS. 12A-12D show profiles measured with a surface roughness
measuring device with respect to ground flat surfaces;
FIG. 13 shows the relationship between intensity detected by the
sensor head and gap distance with respect to the ground flat
surfaces;
FIG. 14 shows the correlation between the maximum intensity
obtained from FIG. 13 and the gap distance;
FIGS. 15A-15E show profiles measured with a surface roughness
measuring device with respect to milled flat surfaces;
FIG. 16 shows the relationship between intensity detected by the
sensor head and gap distance with respect to the milled flat
surfaces;
FIG. 17 shows the correlation between the maximum intensity
obtained from FIG. 16 and the gap distance;
FIGS. 18A-18D show profiles measured with a surface roughness
measuring device with respect to curved ground surfaces;
FIG. 19 shows the relationship between intensity detected by the
sensor head and gap distance with respect to the curved ground
surfaces;
FIG. 20 shows the correlation between the maximum intensity
obtained from FIG. 19 and the gap distance; and
FIG. 21 shows surface roughness monitoring steps in accordance with
an embodiment of the invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
FIGS. 1A and 1B are a sectional view and a bottom view of a
fiber-optic probe 1 used in an embodiment of the present invention.
The probe 1 is the same as that used in the measuring apparatus for
measuring three-dimensional shape proposed earlier by the inventors
and disclosed in U.S. Pat. No. 5,410,410. The fiber-optic probe 1
comprises a probe base 11 and a case 12 serving as a support body
for attachment to a CNC or other such machine tool. Five sensor
heads 2 are embedded in the probe base 11. One of the sensor heads
2 is disposed at the center of the tip of the probe base 11, and
the other four sensor heads are disposed with their head surfaces
inclined to surround the central sensor head.
As shown in the front sectional view of FIG. 2A and the bottom view
of FIG. 2B, each sensor head 2 comprises nine fibers embedded in a
head base 21. The fiber 22 at the center is a light-emitting fiber,
and has a SELFOC microlens 23 attached the tip thereof. Eight
light-receiving fibers 24 are symmetrically disposed with respect
to the emitting fiber 22 at the center. The inner four receiving
fibers 24Ni, 24Si, 24Ei and 24Wi are disposed on intersections
between a circle Ci of radius ri and x and y axes passing through
the center of the head surface, and the outer four receiving fibers
24No, 24So, 24Eo and 24Wo are disposed on intersections between a
circle Co of radius ro and the x and y axes. Fibers having an NA of
0.47 are used as the fibers 22, 24. As the light source coupled
with the emitting fiber 22 there is used a compact, high-output LED
(wavelength: 637 nm).
The end surface (emitting end) of the microlens 23 and the end
surfaces (detecting ends) of the light-receiving fibers 24 are
aligned in the same plane. The distance ri between the emitting
fiber 22 and inner receiving fibers 24Ni-24Wi and the distance ro
between the emitting fiber 22 and the outer receiving fibers
24No-24Wo exert a large effect on the shapes of the received light
intensity versus gap distance curve, as explained later, and this
is directly related to the dynamic characteristics of the sensor
head. In the actually fabricated sensor head, 2ri=2.75 mm and
2ro=5.25 mm, while the diameter of the light-receiving fibers 24
was 0.75 mm, that of the light-emitting fiber 22 was 0.5 mm and
that of the microlens 23 was 1.0 mm.
The fiber bundles 20 of the individual sensor heads 2 are led to
the outside through the case 12, as shown in FIG. 1A, and connected
to the light source and a photosensor.
FIG. 3 shows a system configuration for conducting surface
roughness monitoring. The light-emitting fiber 22 of the
fiber-optic probe 1 is coupled with an LED 31 and the
light-receiving fibers 24 are coupled with a photosensor 32. The
LED 31 is driven by an LED driver 33 controlled by a computer 36.
The output of the photosensor 32 is amplified, subjected to
filtering and other such processing by a signal processor 34,
converted to digital data by an A/D converter 35, and input to the
computer 36. When the fiber-optic probe 1 is attached to a
computer-controlled machine tool, the computer 36 is the control
computer of the machine tool.
In the present invention, surface roughness monitoring is conducted
by detecting the reflected light intensity of the surface to be
measured using the fiber-optic probe 1. Although the probe 1 of
FIG. 1 is equipped with multiple sensor heads 2 for the purpose of
three-dimensional shape measurement, monitoring of the surface
roughness of a single surface can be performed by using only a
single sensor head, e.g., the center one. The principle of surface
roughness monitoring using a single sensor head will now be
explained in detail.
Reflected light intensity ordinarily depends on numerous factors
such as the reflectivity and roughness of the surface, the surface
texture orientation and the like. As regards the machined surface
of a specific sample, the reflected light intensity is affected
mainly by the machining process, the surface roughness and the
texture orientation. Generally, scattering from a surface should be
treated using vector scattering theory, but unfortunately, the
vector methods are extremely tedious and prone to
misinterpretation. There are two possible alternatives. One is the
scalar theory, the other is based on geometric optics. If the
surface roughness is much smaller than the wavelength of the
incident light, the geometrical optics can be adapted. FIGS. 4A-4C
show three different types of surface scattering: (a) reflection
from a specular surface without scattering, (b) scattering from a
diffuse surface, and (c) scattering from a surface of mixture of
specular and diffuse surface.
For most engineering surface, the roughness is greater than the
wavelength of the incident light source for such kind of
measurement, the whole surface can not be treated as a
geometrically smooth surface. However, such a surface can be
treated as a combination of a number of small facets, and for each
facet, geometric optics applicable provided the edge effect is
ignored. The facet method is not easy, however, since the
quantitative relationship between reflected light intensity and
surface roughness is hard to obtain since both height and slope
information of each facet are involved.
In our approach, therefore, the following assumptions are made:
(1) The light intensity distribution reflected from a surface is
approximated by an ellipse.
(2) The total incident light intensity is approximated by the area
of the ellipse and the scattering property is represented by the
shape of the ellipse, for example, by the ratio of the semi-axes a,
b of the ellipse, so that, as shown in FIGS. 5A-5C, the bigger is
the ratio a/b, the smoother is the surface.
(3) The scattering property is fully determined by the surface
roughness and the texture orientation for the same material and the
same machining process.
(4) Based on the above three assumptions, the surface can be
treated as a geometrically smooth surface.
With the above four assumptions, the reflected light intensity can
be related to the surface roughness of the surface to be
measured.
The ellipses of different shapes shown in FIGS. 5A-5C can be
produced by a simulation model according to the above assumptions
and a correlation between the surface roughness and the ratio of
the semi-axes a, b.
As shown in FIG. 6, the beam 61 emitted from the lens 23 of the
sensor head 2 is conical in shape and all rays of the beam 61 are
reflected from the surface 63 to be measured and form a reflection
intensity distribution of an ellipse 62 based on the above
assumptions.
An experimental equation representing the beam intensity I (x, z)
was obtained as the following equation (1) from measured results
which is shown in FIGS. 7A and 7B (Yamazaki, Kee Sein Lee, et al.,
1993, Non-contact Probe for Continuous Measurement of Surface
Inclination and Position Using Irradiation of Light Beam, Annals of
the CIRP, Vol.). ##EQU1##
The principle of light intensity detection is shown in FIG. 8. In
FIG. 8, the light-receiving state is shown with reference to the
two light-receiving fibers 24Ei, 24Eo on the y axis of the head
surface shown in FIG. 2B. Whether or not reflected light is
detected by a light-receiving fiber depends on the fiber diameter
and the critical angle .alpha.. The intensity that can be detected
by the light-receiving fiber is represented by the detectable area
in the reflected intensity ellipse. To determine the detectable
area, we must consider the shaded area in FIG. 8 which are the
intersection area of the ellipse and the straight line segments
from the receiving fibers. If a shaded area within the critical
angle .alpha. of the receiving fiber, the area is considered to the
detectable area and can be used for simulating the detected light
intensity by the sensor head. The detectable area can be calculated
using the following formula (2): ##EQU2## where a and b are the
semi-axes of the ellipse of the reflected light intensity
distribution and can be chosen according to the reflection
characteristic of the surface to be measured. The integral can be
calculated using the following equation (3): ##EQU3##
A detectable region of the ellipse exists for each of the 8
independent light-receiving fibers, and these are summed. Our
previous work has shown that the summation of the detectable areas
such calculated and the actual intensities detected by each
receiving fiber had a very close agreement (Y. Yang and K.
Yamazaki, 1996, Error Analysis by Simulation for a Fiber Based
Non-contact Measurement Probe System, Proceedings of ASPE Annual
Meeting, 1996). Premised on the principle of reflected light
intensity set out above, the concrete relationship among surface
roughness, detected intensity, gap distance and the like, which is
the premise underlying the monitoring of surface roughness
according to the present invention, will now be explained. The sum
of the outputs detected by the light-receiving fibers when the
to-be-measures surface is illuminated by light from the sensor head
will hereinafter be referred to as simply the "detected
intensity."
Relation Between Detected Intensity and Surface Roughness
The quantitative relationship between the detected intensity of the
sensor head and the diameter ratio a/b of the ellipse was
determined by simulation using the above developed method. FIG. 9
shows the relationship.
In FIG. 9, it can be seen that the detected intensity can not
monotonously related to the ratio a/b for the whole range of the
ratio shown in figure, however, it is either monotonously
increasing or decreasing in some specific intervals of the ratio.
For example, the detected intensity increases monotonously when the
ratio increases from 0.05 to about 1.4, which suggests that a
correlation between the detected intensity and the roughness can be
used to determine the roughness of the sample surface being
measured. However, FIG. 9 also implies that the method of the
present invention may not valid for some ranges of roughness
values.
Relation Between Detected Intensity and Surface Texture
Orientation
Different machine processes will produce different textures on the
surface machined. Usually, the scattering intensity distribution
depends on the scattering angle, and there will be more scattering
in the direction of the surface where the texture is roughest. For
example, parallel grooves in a machined surface will scatter almost
entirely at right-angles to the direction of the grooves. In other
words, the machined surfaces are non-isotropic in terms of scatter.
In this case, texture orientation should be taken in consideration
when determining surface roughness using scattering methods. In the
context, we use the term "surface texture orientation" to mean the
relative angle position of two coordinates system xh, yh and xs, ys
as shown in FIG. 10. The first system xh-yh is the sensor head
coordinate system, the origin is attached at the center of the
sensor head, with its z axis coincided with the longitudinal axis
of the head. The second system xs-ys is the sample surface
coordinate system, the origin of the system is fixed at a
measurement position of the surface, with its z axis coincided with
the normal of the surface at the measurement point. Obviously, a
method which is independent of the surface texture orientation is
preferable for on-line machining process monitoring.
In the method of the present invention, there are eight receiving
fibers in the sensor head, four of them are located in north-south
direction, the other four in east-west direction. For different
orientation of the surface texture, the intensity detected by each
receiving fiber is different, however, the sum of the intensities
received by the fibers in both directions remains the same at the
same gap distance. FIGS. 11A and 11B show the results of gap
distance g vs. detected intensity curve against texture orientation
angles in the range of .theta.=0.degree. to 90.degree. for two
turning surfaces. From FIGS. 11A and 11B, it can be seen that the
peak value of the detected intensity in the gap distance vs.
intensity curve is pretty much the same for every orientation angle
of .theta.=0.degree.-90.degree.. Therefore, the peak value of the
detected intensity in a predetermined range of the gap distance
(hereinafter referred to simply as the "maximum intensity") can be
determined by the gap distance g and the roughness of the surface
regardless of the texture orientation.
Relation Between Detected Intensity and Gap Distance
Simulation and actual measurement how that the detected intensity
depends not only on the roughness but also on the gap distance g
between the sensor head and the surface to be measured. Actually,
the later has a more substantial influence on the detected
intensities. Therefore, in order to uniquely relate the detected
intensity to surface roughness, measurement should be taken at the
exact gap distance at which the reference measurement is made. This
would be very difficult in practical situation and prone to
introduce calibration error. Fortunately, the sensor head has the
following favorable feature: Although the detected intensity are
different at different gap distance for the same surface, the
maximum intensity is indeed uniquely associated with the surface
itself. For the same type of material and the same type of
machining procedure, the maximum intensity are always occurred at
the approximately same gap distance. The gap distance associated
with the maximum intensity rely primarily on the reflectivity of
the surface. Our experiments showed that the gap distances
regarding to the maximum intensity are between 3 mm and 5 mm for a
wide range of reflectivity of sample surfaces. Therefore, once the
correlation between the maximum intensities and the gap distance is
obtained, they can be used to determine the roughness of the
surface in question. In the experimental configuration, the sensor
head was attached to the column of the coordinate measuring machine
(CMM) so as to be movable. The maximum intensity can be easily
determined through measurement against every gap distance during
the moment of the sensor head.
Relation Between Detected Intensity and Roughness Value (Center
Line Average Roughness) Ra
The detected intensity can be related to different parameters of
surface roughness such as Ra (average of the absolute value of the
deviation between the average line and the measured curve), Rq (rms
of the deviation between the average line and the measured curve),
Rp (maximum ridge height) or the like. In our study, a relationship
between the detected intensity and the roughness Ra is
established.
FIGS. 12A-12D show the profiles of four flat ground surfaces
(Ra=0.07, 0.1, 0.2, 0.7) measured by Surftest 501 (product of
Mitutoyo Corporation). The measurement conditions are: cut-off
wavelength .lambda.c=0.8 .mu.m; measurement number.times.4;
horizontal multiplication.times.20; and vertical
multiplication.times.10,000. FIG. 13 shows the measurement curve of
detected intensity vs. gap distance. FIG. 14 is the relation curve
between the detected maximum intensity and surface roughness
Ra.
FIGS. 15A-15E show the profiles of five flat milled sample surfaces
(Ra=0.98, 2.09, 3.64, 5.46, 6.69) measured by Surftest 501. FIG. 16
shows the measurement curve of detected intensity vs. gap distance
for those sample surfaces (with those for the cases of Ra=2.09,
5.46 omitted). FIG. 17 is the relation curve between the detected
maximum intensity and the roughness Ra.
FIGS. 18A-18D show the profiles of four curved ground sample
surfaces (Ra=0.08, 0.29, 0.66, 1.24) measured by Surftest 501. FIG.
19 shows measurement curves of detected intensity vs. gap distance
for the sample surfaces. FIG. 20 is the relation a curve between
the detected maximum intensity and the roughness Ra for the curved
ground sample surfaces.
It can be seen from the above results that the maximum intensity is
correlated to roughness value for any type of surface irrespective
of machining type. This correlation can be used to determine the
roughness of a surface with the aid of pre-calibration using
reference roughness measurement results.
Based on the above described knowledge, monitoring of surface
roughness during machining of a given sample using a specific
machine tool is performed as follows. During actual surface
monitoring, the head surface of the sensor head is maintained
parallel to the measurement surface. As taught by U.S. Pat. No.
5,410,410, the sensor head used in the present invention has the
capability to detect deviation from parallel with the measurement
surface. Therefore, using this capability, ready adjustment in the
case of deviation from parallel can be made easily.
FIG. 21 outlines the surface roughness monitoring steps. Steps S1
to S3 are calibration steps. In the pre-measuring step S1, the
probe is used to perform measurement with respect to a plurality of
reference samples obtained under a plurality of different
processing conditions, and a first correlation between gap distance
and detected intensity is found for each. As is clear from FIGS.
14, 17 and 20, from these correlations there can be obtained second
correlations between maximum intensity and surface roughness value,
which differ with type of machining, and, therefore, in step S2,
the second correlations of the maximum intensity vs. surface
roughness are searched to be stored in a memory or the like.
Next, in the gap adjusting step S3, the probe is set to such a gap
distance that the maximum intensity is obtained, based on the first
correlation of detected intensity vs. gap distance obtained in the
pre-measuring step S1 for the reference sample surface machined
under the processing conditions to be monitored. As can be seen
from FIGS. 11A and 11B, although the detected intensity vs. gap
distance curve differs with the processing conditions, the gap
distance at which the maximum intensity is obtained is
substantially constant so long as the processing conditions are
constant.
Step S4 is the roughness monitoring step for monitoring the surface
roughness for to-be-measured samples accompanying the actual
machining, In this step S4, the maximum intensity of the machined
surface at the gap distance set in step S3 is monitored in real
time, and roughness is discriminated based on the second
correlation between maximum intensity and roughness value stored in
the memory beforehand.
Because of the simplicity of the measurement method, it is easy to
implement the measurement method into practical application. For
example, the sensor head can be attached to the spindle of a CNC
machine tool just like a regular tool to allow the required
movement, and the computation can be performed by the computer of
the controller of the CNC machine. By such an application, on-line
surface roughness monitoring and control can be performed.
Therefore, The method of the present invention may be a suitable
approach to surface quality monitoring for productive machining
system.
Another attractive feature of the method of the present invention
is that the same measuring head can also be used to autonomously
measure both incline angle and position coordinate for a sculptured
surface in a non-contact manner with the aid of a coordinate
measuring machine and related software and algorithms which were
developed early by the inventor. This provides a potential
innovation to integrate non-contact surface coordinate measurement
and roughness measurement into one single measurement probe, or
into one single measuring machine, which, obviously, will be very
helpful to the development of integrated, multi-purpose measuring
machines.
The present invention thus provides the following effects:
(a) Simple, fast, on-line, easy to implement and easy to perform
surface roughness measurement system is provided for productive
manufacturing systems such as CNC machine tools and machining
centers.
(b) It does not have the drawbacks of the many other non-contact
surface roughness measurement methods proposed heretofore.
(c) Because of the simplicity of implementation, this fiber-optic
method may find prospective applications in the future.
(d) By properly arranging fiber sensors, the sensor head is
independent of the texture orientation of the sample surfaces.
(e) For the same type of surface, the detected maximum intensity
has a good correlation to the roughness values of the sample
surfaces.
(f) The method of the present invention provides a potential
possibility to incorporate surface roughness measurement and
surface position coordinate and inclination angle measurement into
one single measurement probe based on the previous research result
on autonomous sculptured surface measurement system achieved by the
inventor.
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